Inventory

LITERATURE REVIEW

This research centers on development of spare part inventory management

system. Current researches in spare part inventory management include by Li & Kuo ,

Porras & Dekker, Vereecke & Verstraeten , Baron et. al., Dekker et al. ,

Aronis et al., Jin & Liao, Cobbaert and Qudheusden , Kattan and Adi ,

Chou andHuang, and Mohd-Lair et al. . Li & Kuo , in their journal titled

Automobile Spare parts in a central warehouse, used the Enhanced Fuzzy Neural

Network (EFNN) and Enhanced Fuzzy Neural Network with randomly initialized

connection weights(EFNNR) as their inventory control method.

They compared the two techniques to see their differences. They found that the EFNN

is much better than EFNNR because it avoids out of stock at the price of least stock cost.

Porras & Dekker said that ex-ante is more relevance than ex-post, which is hard to

be implemented. They used the Willemain’s bootstrap method, Empirical distribution of

lead time demand, Normal Distribution, Poisson Distribution and (s,nQ) inventory

model. They found that the inventory models can save money and improve service

levels. Vereecke & Verstraeten used integration of inventory model with two

demand classes (r, r, Q) model with poison distribution. The Spare Part Inventory

Management System (SPIMS) for the A-ARAMCO Enterprise.

This research used service level, average demand, costs and lead time as their

performance measure. They found the reorder point that gave satisfying

result in term of the service levels. Baron et. al. used the stochastic (s, S) approach in

their research. They considered the problem with perishable items (i.e. medicine or

food with expiration date). The performance of the above approach was measured

using costs and lead time of the inventories. The numerical study on the heuristics

shows that they are accurate. When the exact analysis is not possible and the lead time

is relatively short,...